Improvements in the estimation of daily minimum air temperature in peninsular Spain using MODIS land surface temperature

Air temperature (T_a) is a key variable in many environmental risk models and plays a very important role in climate change research. In previous studies we developed models for estimating the daily maximum (T_max), mean (T_mean), and minimum air temperature (T_min) in peninsular Spain over cloud-free land areas using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Those models were obtained empirically through linear regressions between daily T_a and daytime Terra-MODIS land surface temperature (LST), and then optimized by including spatio-temporal variables. The best T_mean and T_max models were satisfactory (coefficient of determination (R²) of 0.91–0.93; and residual standard error (RSE) of 1.88–2.25 K), but not the T_min models (R² = 0.80–0.81 and RSE = 2.83–3.00 K). In this article T_min models are improved using night-time Aqua LST instead of daytime Terra LST, and then refined including total precipitable water (W) retrieved from daytime Terra-MODIS data and the spatio-temporal variables curvature (c), longitude (λ), Julian day of the year (JD) and elevation (h). The best T_min models are based on the National Aeronautics and Space Administration (NASA) standard product MYD11 LST; and on the direct broadcast version of this product, the International MODIS/AIRS Processing Package (IMAPP) LST product. Models based on Sobrino’s LST1 algorithm were also tested, with worse results. The improved T_min models yield R² = 0.91–0.92 and RSE = 1.75 K and model validations obtain similar R² and RSE values, root mean square error of the differences (RMSD) of 1.87–1.88 K and bias = 0.11 K. The main advantage of the T_min models based on the IMAPP LST product is that they can be generated in nearly real-time using the MODIS direct broadcast system at the University of Oviedo.     

Forest biomass estimation through NDVI composites. The role of remotely sensed data to assess Spanish forests as carbon sinks

The present study is focused on the capabilities of remote sensing data and techniques to help in the monitoring of forest ecosystems as carbon sinks. It will attempt to find statistical relationships between satellite‐derived NDVI (Normalized Difference Vegetation Index) data from SPOT‐VEGETATION and NOAA‐AVHRR and field measurements from the Spanish National Forest Inventory on the geographical basis of provinces. Statistically significant relationships were obtained when correlating the aforementioned datasets. These relationships were then used to predict forest biomass at a national level, in order to obtain updated forest information between consecutive National Forest Inventories.     

Using PCA transformation to remove the tenuous cloudiness effect in multispectral satellite sensor images

An algorithm using no external data is proposed for removing the inhomogeneous effect of thin cloudiness and other aerosols on multispectral satellite sensor images such as Landsat Enhanced Thematic Mapper (ETM) images. The method consists of a series of digital processing operations and is based on principal component analysis (PCA). The goal is to generate, for every original band, a new band whose digital number (DN) values are related only to the atmospheric intensity effect. An example is shown and some limitations are discussed.     

Grass species differentiation through canopy hyperspectral reflectance

This study attempts (1) to evaluate the capability of hyperspectral reflectance to differentiate C₃ and C₄ grass species, both in isolation and in mixed canopies; (2) to identify the critical spectral ranges that differentiate the two groups and individual species within them; and (3) to determine if there is temporal variation in these capabilities. During one year, hyperspectral reflectance of C₃ and C₄ grass species was measured both in single-species and in mixed canopies. Spectral bands with higher differentiating potential were identified and species classified. For single-species canopies, hyperspectral reflectance differentiated the two functional groups and most species in all seasons. In mixed canopies, it underestimated the fractional cover of the C₄ component. The green, red, and near infrared above 820 nm spectral ranges were critical both for species and functional group differentiation. In conclusion, hyperspectral information was useful to differentiate pure canopies, but the differentiation algorithms were season-specific. Additionally, we need to improve our understanding of interactive effects of species in order to accurately estimate the composition of assemblages.     

A definition of column reduced proper rational matrices

The aim of this work is to develop analogue concepts of column reduced polynomial matrices for proper rational matrices. A definition of column reducedness for a class of proper rational matrices is proposed and the properties of such matrices are studied, in particular reduction to column reduced form by elementary operations over the ring of proper rational functions, and the relationship between the degrees of the invariant factors of a column reduced matrix and the so-defined column indices. The physical significance of such matrices in terms of their finite structure is explained; this interpretation completely complements the physical interpretation of a column reduced polynomial matrix. An application of the properties of column reduced proper rational matrices to the decoupling problem is also presented: the infinite structure which can be obtained while decoupling a linear multivariable system by non-regular static state feedback is completely characterized.     

A novel methodology to solve the CQLF problem for a finite set of stable second-order systems

A new methodology to provide conclusive information about the existence/non-existence of a common quadratic Lyapunov function (CQLF) for a finite set of stable second-order systems is presented. Despite the high complexity of the CQLF problem, even in the case of N second-order systems, the results presented in this paper have a very simple and intuitive theoretical support, including topics such as classical intersection of convex sets and properties of convex linear combinations. Illustrative examples to show the performance of the proposed methodology are provided.     

Vegetation responses to precipitation and temperature: a spatiotemporal analysis of ecoregions in the Colorado River Basin

Predicting vegetation response to precipitation and temperature anomalies, particularly during droughts, is of great importance in semi-arid regions, because ecosystem and hydrologic processes depend on vegetation conditions. This article studies vegetation responses to precipitation and temperature in 10 ecological regions within the semi-arid Colorado River Basin (CRB). The Normalized Difference Vegetation Index (NDVI) from Global Inventory Modeling and Mapping Studies (GIMMS) database and the Standardized Precipitation Index (SPI) and temperature series from Parameter-Elevation Regressions on Independent Slope Models (PRISM) database were jointly evaluated for the period 1986–2006, using Multichannel Singular Spectrum Analysis (MSSA) to determine common oscillations and significant lags in vegetation response to seasonal and annual precipitation and temperature. Results show high correlations between lagged SPI series and standardized NDVI: from 1-month lag in the warm deserts (Sonora, Chihuahua and Mojave) to two months in the Temperate Sierras and Semi-Arid Highlands and three months in the Colorado and Arizona/New Mexico Plateaus and the Western Cordillera. Temperature anomalies are negatively correlated to NDVI in the lower CRB and positively correlated in the upper CRB. Notably, we see a basin-wide response to SPI anomalies, and consequently, the identified latitudinal and altitudinal lags between SPI and NDVI will allow an early, basin-wide assessment of lagged vegetation responses to precipitation along the CRB ecoregions.     

Prediction of the n‐hexane/water and 1‐octanol/water partition coefficients for environmentally relevant compounds using molecular simulation

In recent years molecular simulation has emerged as a useful tool to predict physical properties of complex chemical systems. A methodology to estimate the n‐hexane/water and 1‐octanol/water partition coefficients of environmentally relevant solutes, namely substituted alkyl‐aromatic molecules, chlorobenzenes, polychlorinated biphenyls (PCBs) and polychlorinated diphenyl ethers (PCDEs) using molecular simulation is elucidated here. The partition coefficients are calculated based on the absolute solvation Gibbs energies in each phase which are estimated from molecular dynamics simulations employing the thermodynamic integration approach. Very encouraging results, with average absolute deviations of 0.4 log P units are presented. Consequently, this molecular‐based approach with a strong physical background can provide reliable prediction of the partition coefficients in different solvent pairs without the a priori knowledge of experimental data. © 2011 American Institute of Chemical Engineers AIChE J, 58: 1929–1938, 2012     

Studies on some properties of poly(phenylene sulphide)

Poly(phenylene sulphide) was synthesized by a direct method. Benzene and elemental sulphur were used as substrates, and aluminium chloride as a catalyst. The obtained final product was characterized by IR, VIS-UV, wide angle X-ray and mass spectroscopy, thermal, and elemental analyses. On the base of the analytical methods the molecular structure of the obtained polymer was discussed.     

Production, purification and characterisation of polysaccharides from Pleurotus ostreatus with antitumour activity

BACKGROUND: Mushroom polysaccharides play an important role in functional foods because they exhibit biological modulator properties such as antitumour, antiviral and antibacterial activities. The present study involved the production, purification and characterisation of intracellular and extracellular free and protein‐bound polysaccharides from Pleurotus ostreatus and the investigation of their growth‐inhibitory effect on human carcinoma cell lines. RESULTS: Several fermentation parameters were obtained: batch polysaccharide productivities of 0.013 ± 8.12 × 10^?5 and 0.037 ± 0.0005 g L^?1 day^?1 for intracellular and extracellular polysaccharides respectively, a maximum biomass concentration of 9.35 ± 0.18 g L^?1, P_max = 0.935 ± 0.018 g L^?1 day^?1, µ_max = 0.218 ± 0.02 day^?1, Y_EP/X = 0.040 ± 0.0015 g g^?1 and Y_IP/X = 0.014 ± 0.0003 g g^?1. Some polysaccharides exhibited superoxide dismutase (SOD)‐like activity of 50‐200 units. Fourier transform infrared analysis of the polysaccharides revealed absorption bands characteristic of such biological macromolecules. Cytotoxicity assays showed that both intracellular and extracellular polysaccharides exhibited antitumour activity towards several tested human carcinoma cell lines in a dose‐dependent manner. CONCLUSION: The polysaccharides of P. ostreatus exhibited high SOD‐like activity, which strongly supports their biological effect on tumour cell lines. The extracellular polysaccharides presented the highest antitumour activity towards the RL95 carcinoma cell line and should be further investigated as an antitumour agent. Copyright © 2012 Society of Chemical Industry